Vector performance estimation for Cray X-MP/Y-MP supercomputers, part 2

Abstract

The conventional method of assessing supercomputer performance by measuring the execution time of software has many shortcomings. First, effort is required to write and debug the software. Second, time on the machine is required, and additional effort is needed to verify the validity of the test. Third, alterations to the algorithm require changing the code and retiming. Fourth, a black box approach to determining machine performance leaves the user with little confidence in how well the software was optimized. We present a pencil and paper methodology for computing the execution time of vectorized loops on a Cray Research X-MP/Y-MP. With this methodology a user can accurately compute the processing rate of an algorithm before the software is actually written. When several implementations of an algorithm are designed, this methodology can be used to select the best one for development, preventing wasted coding effort on less efficient implementations. Since this methodology computes optimal machine performance, it can be used to verify the efficiency of compiler translation. Changes to algorithms are easily appraised to determine their effect on performance. While the purpose of the methodology is to compute an algorithm's execution time, a side benefit is that this technique induces the user to think in terms of optimization. Bottlenecks in the code are pinpointed, and possible options for increased performance become obvious. At E-Systems, this methodology has become an integral part of the software development of vector-intensive code. This article is written specifically for Cray Research X-MP/Y-MP supercomputers, but many of the general concepts are applicable to other machines and therefore should benefit a number of supercomputer users.